def main():
(x, y) = LSM.data()
(xwn, ywn) = LSM.data(Noise=True)
lsm = LSM.LSM_L2(6)
lsm.fit(x, y)
lsm2 = LSM.LSM_L2(6)
lsm2.fit(xwn, ywn)
tics = 2 * pi * arange(0, 1, 0.02)
lw = 5 #line width
plt.subplot(211)
plt.legend()
plt.plot(x, y, 'ro', ms=10)
plt.plot(tics, sin(tics), linewidth=lw, label="sin")
plt.plot(tics, lsm.predict(tics), linewidth=lw, label="fitting")
plt.legend(loc='lower right')
plt.subplot(212)
plt.xlim(0, 2 * pi)
plt.ylim(-2, 2)
plt.legend()
plt.plot(xwn, ywn, 'ro', ms=10)
plt.plot(tics, sin(tics), linewidth=lw, label="sin")
plt.plot(tics, lsm2.predict(tics), linewidth=lw, label="fitting")
plt.legend(loc='lower right')
plt.show()
def main():
(x,y) = LSM.data()
(xwn, ywn) = LSM.data(Noise=True)
lsm = LSM.LSM_L2(6)
lsm.fit(x,y)
lsm2 = LSM.LSM_L2(6)
lsm2.fit(xwn,ywn)
tics = 2*pi*arange(0,1,0.02);
lw = 5 #line width
plt.subplot(211)
plt.legend()
plt.plot(x,y, 'ro', ms=10)
plt.plot(tics,sin(tics), linewidth=lw, label="sin")
plt.plot(tics,lsm.predict(tics), linewidth=lw, label="fitting");
plt.legend(loc = 'lower right')
plt.subplot(212)
plt.xlim(0,2*pi)
plt.ylim(-2,2)
plt.legend()
plt.plot(xwn,ywn, 'ro', ms=10)
plt.plot(tics,sin(tics), linewidth=lw, label="sin")
plt.plot(tics,lsm2.predict(tics), linewidth=lw, label="fitting");
plt.legend(loc = 'lower right')
plt.show()
def main():
(x,y) = LSM.data()
(xwn, ywn) = LSM.data(Noise=True)
lsm = LSM.LSM_L2(M=7, l=2.)
tics = 2*pi*arange(0,1,0.02);
lw = 5 #line width
ls = power(7., range(-2,3))
print(ls)
for idcs in range(len(ls)):
plt.subplot(len(ls),1,idcs+1)
plt.xlim(0,2*pi+2)
plt.ylim(-2,2)
plt.legend()
plt.plot(xwn,ywn, 'ro', ms=10)
plt.plot(tics,sin(tics), linewidth=lw, label="sin")
lsm.l = ls[idcs]
lsm.fit(xwn,ywn)
plt.plot(tics,lsm.predict(tics), linewidth=lw, label='l={:.1}'.format(ls[idcs]));
plt.legend(loc = 'lower right')
plt.show()
def main():
(x, y) = LSM.data()
(xwn, ywn) = LSM.data(Noise=True, NL=0.3, N=10)
lsm = LSM.LSM_L2(M=7, l=2.)
tics = 2 * pi * arange(0, 1, 0.02)
lw = 5 #line width
ls = array([0.0, 0.1, 10, 100])
print(ls)
for idcs in range(len(ls)):
plt.subplot(len(ls), 1, idcs + 1)
plt.xlim(0, 2 * pi + 2)
plt.ylim(-2, 2)
plt.legend()
plt.plot(xwn, ywn, 'ro', ms=10)
plt.plot(tics, sin(tics), linewidth=lw, label="sin")
lsm.l = ls[idcs]
lsm.fit(xwn, ywn)
plt.plot(tics,
lsm.predict(tics),
linewidth=lw,
label='l={:.1}'.format(ls[idcs]))
plt.legend(loc='lower right')
plt.show()
